Traditional diagnostic methods are often inconvenient, labor intensive, and expensive because they require in-depth analysis by trained experts. In the realm of personal diagnosis, for example, a subject suffering from an illness or other health condition typically has to visit a medical professional to diagnose his/her condition. This may require scheduling an appointment with the professional, traveling to the professional's office, waiting to be seen by the professional, finally being examined, and possibly returning to the office for subsequent examinations. The examination itself may require the subject to answer many questions and perform a large battery of tests before a proper diagnosis is obtained. Many times this process may require more effort and be more expensive than the subject is willing to accept. Accordingly, the subject may choose to not bother with the diagnosis. Thus, a convenient means for the subject to obtain a preliminary diagnosis from a remote location without answering an overwhelming number questions would be beneficial.
In aspects outside of personal diagnosis, traditional analysis typically involves collecting empirical data, distilling the data, and drawing conclusions from the data, wherein the conclusions may be used in the future for diagnostic purposes. In order to make correct diagnoses from these conclusions, often a large quantity of initial empirical data may be required. Large amounts of data compound the problem of distilling and analyzing the data. As a result, highly skilled individuals must spend valuable time collecting, organizing, and interpreting the data to glean useful information from it.
In another diagnosis example in the field of chemical analysis, a researcher searching for unique properties of chemical compounds (or chemical compounds having such properties) may conduct numerous experiments and collect a massive quantity of data. In order for the researcher to extract useful information from the data, he/she has to perform the tedious task of organizing and evaluating the experimental results. Therefore, it would be beneficial to provide a means to organize data quickly and accurately. Once data is properly organized, the researcher may find the data useful, in at least the chemical analysis example, to diagnose properties of additional samples.
Although the foregoing background discussion is directed primary to diagnostics, it will become apparent in the following description that many aspects of the present invention have applicability in fields other than those involving a diagnosis. Accordingly, the background discussion should be considered to be exemplary of a few of many possible background issues that could be addressed.